I am a Research Scientist at Reality Labs Research, Meta. I work on developing efficient planning and reinforcement learning algorithms to enable household assistive agents in AR/VR to provide guidance to users for day-to-day tasks.
Earlier, I graduated with an MS in Intelligent Robotics and a Ph.D. in Computer Science from the University of Southern California (USC) in May 2021. I was advised by Yan Liu in the Melady Lab. My research was primarily focused on prediction and control in multi-agent settings with dense interactions amongst the various agents. I also worked on several projects involving reinforcement learning, continual learning, game theory, robotics, natural language understanding and graph-based relational learning.
Before this, I attended Indian Institute of Technology, Delhi (2010-2014) for my undergraduate degree in Electrical Engineering, with focus on Control Theory and Signal Processing. I was advised by Shouribrata Chatterjee. I was also the Technical Secretary of the Electrical Engineering Society and served as the General Secretary of the Electronics Club during my final year at IIT Delhi.
My broad research interest lies in understanding "understanding" itself. As an ambitious goal, I want to figure out how the human mind works and potentially develop architectures and algorithms for artificial agents to achieve at least the same level of understanding as humans one day. Consequently, I work on reinforcement learning and deep learning to design agents capable of autonomous planning and learning in multi-agent settings. My research interests broadly span deep reinforcement learning, continual learning, planning, multi-agent learning, natural language understanding and robotics.